This invention relates to microarrays. It relates more particularly to a method and apparatus for locating spots in a microarray image, also referred to as image segmentation.
A microarray is an array of very small samples of chemical or biochemical material drawn from reservoirs by a spotting instrument or spotter and deposited as a grid of many such spots on a solid substrate such as a glass microscope slide. When the microarray is exposed to selected probe material including a label molecule such as a fluorophore, the probe material selectively binds to the target sites only where complimentary binding spots are present through a process called hybridization thereby providing an assay. The microarray may then be scanned by a florescence-detecting scanning instrument or scanner to produce a pixel map of fluorescent intensities. To obtain statistically derived numerical data from the usually non-uniform and noisy fluorescent images of the spots, the scanning is done at high resolution so that each spot is represented by many pixels, e.g. up to 100 per spot. This fluorescent intensity map may be analyzed using special purpose quantitation algorithms which reveal the relative concentrations of the fluorescent probes and hence the level of gene expression, protein concentration, etc. present in the assayed probe samples. This quantization step is usually performed on an image analysis computer or workstation and results in a set of numerical data which includes at least a numerical value of the representative probe signal for each microarray spot in the image.
The most common type of spotting instrument is the pin spotter which includes a plurality of printing pins arranged in a pattern on a robot-actuated print head. A typical print head may contain, say, sixteen pins arranged in a rectangular grid. The location tolerances between the print head and the printing tips of the individual pins is typically many tens of microns, which is larger than the typical robot's print head positioning tolerance of one to three microns. It is because of this and the necessity of avoiding the printing of merged or touching spots on the substrate that microarrays are usually printed as a pattern of sub-arrays or blocks, with one block being printed by each pin. The motion of the spotter's print head is such that each pin prints with a typical spot center-to-center distance within each block of 80 to 150 microns, whereas the spacing between adjacent blocks is typically 1.5 to 10 times larger than that.
This method is also applicable for use with multi-tip, non-contact piezo or ink-jet spotters. Instead of using pins, these instruments use one or more jets to form the spots on the microarray substrate.
The present invention concerns specifically the process of image segmentation or spot location in preparation for microarray quantitation. This is because the quantitation algorithm needs to know which pixels in the vicinity of each microarray spot are to be used to calculate that spot's intensity signal and which pixels, referred to as background pixels, should be excluded from that spot.
To start the spot location or segmentation process, the microarray image is usually displayed on an image analysis computer or workstation monitor. Then, an image of a grid of microarray spot location markers which usually reflect the diameter of the spots is superimposed on the image. This grid may be generated by the spotter and delivered to the work station via a file, e.g. the standard .gal file promulgated by Axon Instruments Co., via a disk, bus or other data transfer means. Alternatively, the nominal grid information, e.g. number of rows and columns in the grid, the grid pattern, nominal spot spacing, etc. may be entered manually by a user via the workstation's keyboard.
A typical grid image may be a pattern of circles constituting the spot location markers with or without grid lines connecting the circles. Alternatively, crosses, polygons or other shapes can represent the markers in the grid image. The grid image is generally moveable on the microarray image by dragging and dropping it using a computer mouse, track ball or other computer pointing device. In some software implementations, individual spot location markers, or marker columns and rows can be repositioned with respect to the microarray image and the rest of the grid by dragging and dropping same.
In practice, a nominal grid rarely aligns well with the underlying scanned microarray image due to the combined effects of various tolerances in the spotting instrument. These include variations in the locations of the pin tips in the spotter's print head, misalignment of the print head with the spotter's x/y motion axes, non-orthogonality of the spotter's motion axes, spotter robot motion accuracy errors, and microarray substrate location errors in the spotter. There also may be scanning mechanism location accuracy errors in the scanner which scans the microarray image during the segmentation process.
Some of these errors are systematic in that they are repeatable for every microarray printed by a particular spotter, some errors are repeatable within a batch of printed arrays and some errors are random. For example, the shape of the outline of each microarray block is determined by the spotter robot's motion, the block size, the interspot distances and whether the block is rectangular or not. Since each block is printed simultaneously with all of the other blocks in the microarray, but with a different pin in the same print head, any deviations from the rectangular geometry within any block are usually identical in all of the other blocks. On the other hand, the location of the overall spot pattern in the image can vary from one array to another due to variations in the positions of the microarray substrates in the spotting instrument. A random spot location error may be caused by random variations in the motion of the print head in a given spotter which may cause small variations in the locations of individual spots within each block of the microarray.
Therefore, it is essential to reconcile the nominal location of each spot location marker in the nominal grid with the actual spot location in the underlying image. This has been done heretofore wholly manually, e.g. using a computer mouse, by moving or rotating a nominal grid of each block in the microarray or the whole array using visual feedback to align the spot location markers in the grid with the spots in the microarray image as displayed on the workstation monitor. For grid/array errors involving more than simple translations and/or rotations of the grid, a user may adjust the positions of individual spot location markers by dragging those markers and/or entire rows or columns of markers. This process is usually effective because the human eye is very sensitive to misalignment of similarly sized objects. However, manual manipulation of individual markers or rows or columns of such markers within the grid association with a given microarray to locate the spots is a tedious and time consuming task, bearing in mind that a is typical microarray may contain thousands of spots.
There do exist various algorithms which perform such spot location automatically, see e.g. U.S. Pat. Nos. 6,349,144 and 6,345,115. Such automating of the spot location process eliminates the painstaking labor involved in the manual methods described above, but the algorithms that are available to do so can produce erroneous results, especially for dim or noisy microarray images, See Marzolf et al., Validation of Microarray Image Analysis Accuracy, Bio Techniques 36:304-308, February 2004. Such automatic spot location techniques are also more likely to fail with increased location errors between the nominal grid markers and the actual spot locations in the microarray image.
In any event, spot location errors, if not corrected before quantitation, can lead to mis-identified spots (analytes) in the analysis of the array or incorrect quantitation results for some spots. Because of these frequent spot location errors with automatic spot location apparatus, manual inspection and correction of the automatic spot location results must often be performed thereby undoing some of the labor saving steps intended through the use of such automatic spot location methods. Even if the automatic methods produce good results, the automatic methods are generally computationally intensive, and thus, time consuming.
Certain automated methods use microarray image projections as discussed in Stanley et al. Microarray Image Spot Segmentation Using the Method of Projections, Biomed.Sci.Instrum. 38:387-392, 2002 and United States patent application Publication U.S. 2004/0001623 to Ugolin et al. Stanley, for example, uses the maximum of each projection to locate a row or column of an array. While this method is not particularly computationally intensive, the method fails when multi-spot artifacts that span multiple rows or columns are encountered. Ugolin describes a more robust method that imposes a Fourier transform on the projections. The Ugolin method is, however, very computationally intensive, and thus slow.
Therefore, what is needed is an automated method and apparatus for locating spots in a microarray image which provides the accuracy and reliability of the manual spot location technique described above thereby avoiding spot location errors, is while doing away with the tedious and time consuming task of manually aligning the nominal grid or individual spot location markers or rows and columns of same on each microarray image, and while also avoiding the long computation times of transform based systems.